{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to Survival Analysis: the Nelson-Aalen estimator"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from lifelines import NelsonAalenFitter\n",
    "\n",
    "plt.style.use('seaborn')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading and preparing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of the DataFrame: (7043, 22)\n",
      "Number of unique users in the DataFrame: 7043\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>customerID</th>\n",
       "      <th>gender</th>\n",
       "      <th>SeniorCitizen</th>\n",
       "      <th>Partner</th>\n",
       "      <th>Dependents</th>\n",
       "      <th>tenure</th>\n",
       "      <th>PhoneService</th>\n",
       "      <th>MultipleLines</th>\n",
       "      <th>InternetService</th>\n",
       "      <th>OnlineSecurity</th>\n",
       "      <th>...</th>\n",
       "      <th>TechSupport</th>\n",
       "      <th>StreamingTV</th>\n",
       "      <th>StreamingMovies</th>\n",
       "      <th>Contract</th>\n",
       "      <th>PaperlessBilling</th>\n",
       "      <th>PaymentMethod</th>\n",
       "      <th>MonthlyCharges</th>\n",
       "      <th>TotalCharges</th>\n",
       "      <th>Churn</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7590-VHVEG</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>1</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>29.85</td>\n",
       "      <td>29.85</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5575-GNVDE</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>34</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>56.95</td>\n",
       "      <td>1889.5</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3668-QPYBK</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Mailed check</td>\n",
       "      <td>53.85</td>\n",
       "      <td>108.15</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7795-CFOCW</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>45</td>\n",
       "      <td>No</td>\n",
       "      <td>No phone service</td>\n",
       "      <td>DSL</td>\n",
       "      <td>Yes</td>\n",
       "      <td>...</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>One year</td>\n",
       "      <td>No</td>\n",
       "      <td>Bank transfer (automatic)</td>\n",
       "      <td>42.30</td>\n",
       "      <td>1840.75</td>\n",
       "      <td>No</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9237-HQITU</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>2</td>\n",
       "      <td>Yes</td>\n",
       "      <td>No</td>\n",
       "      <td>Fiber optic</td>\n",
       "      <td>No</td>\n",
       "      <td>...</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>No</td>\n",
       "      <td>Month-to-month</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Electronic check</td>\n",
       "      <td>70.70</td>\n",
       "      <td>151.65</td>\n",
       "      <td>Yes</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   customerID  gender  SeniorCitizen Partner Dependents  tenure PhoneService  \\\n",
       "0  7590-VHVEG  Female              0     Yes         No       1           No   \n",
       "1  5575-GNVDE    Male              0      No         No      34          Yes   \n",
       "2  3668-QPYBK    Male              0      No         No       2          Yes   \n",
       "3  7795-CFOCW    Male              0      No         No      45           No   \n",
       "4  9237-HQITU  Female              0      No         No       2          Yes   \n",
       "\n",
       "      MultipleLines InternetService OnlineSecurity  ... TechSupport  \\\n",
       "0  No phone service             DSL             No  ...          No   \n",
       "1                No             DSL            Yes  ...          No   \n",
       "2                No             DSL            Yes  ...          No   \n",
       "3  No phone service             DSL            Yes  ...         Yes   \n",
       "4                No     Fiber optic             No  ...          No   \n",
       "\n",
       "  StreamingTV StreamingMovies        Contract PaperlessBilling  \\\n",
       "0          No              No  Month-to-month              Yes   \n",
       "1          No              No        One year               No   \n",
       "2          No              No  Month-to-month              Yes   \n",
       "3          No              No        One year               No   \n",
       "4          No              No  Month-to-month              Yes   \n",
       "\n",
       "               PaymentMethod MonthlyCharges TotalCharges  Churn churn  \n",
       "0           Electronic check          29.85        29.85     No     0  \n",
       "1               Mailed check          56.95       1889.5     No     0  \n",
       "2               Mailed check          53.85       108.15    Yes     1  \n",
       "3  Bank transfer (automatic)          42.30      1840.75     No     0  \n",
       "4           Electronic check          70.70       151.65    Yes     1  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../data/telco_customer_churn.csv')\n",
    "df['churn'] = [1 if x == 'Yes' else 0 for x in df['Churn']]\n",
    "\n",
    "print(f\"Shape of the DataFrame: {df.shape}\")\n",
    "print(f\"Number of unique users in the DataFrame: {df['customerID'].nunique()}\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Nelson-Aalen Estimate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cumulative hazard function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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SxBKaVFZJMGAkJ0+e1KRJkxQXF1cqFAgJCVFMTIw2bdqk8+fPV/p17r//fq1du1bLli2zBDYly6GunPFx5UyiX3/9tdz72rMDj73Pcfv27Xr77bctOyRJkpeXlxo1aqR7771XS5YsKfPaS5cu6cUXX9SxY8fUqlUrvfnmm1bHnT9/Xu+8846WLl1aajewoKAg3X777Tpw4IBlB64/KmsmSclsjrK+b4GBgWXWXdVsfSYls5+c9TNU8r2rXbt2mWNKXruwsFB5eXmlGm2XN6vHmYErAMA+BDYAABhM165dNXnyZJ09e1aJiYlXbb39R7///rsGDBggPz8/TZ8+XV26dCl13tovYJVZNlQRZf0SaG35TFnjnnzySR0/flw33HCDBg8erNatW6tp06aW2RvWlupUxJ133qm6desqISFBp0+flp+fn3766Sf5+/urV69elnElS42kyzt7BQcHO+T17XXw4EENGTJE+fn5at++ve6//35FRkaqadOmCggIUFJS0p8GNm+99ZZ+/PFHBQcHa+bMmZaZFlcqLi7W8OHDlZCQoHr16unRRx9V27Zt1axZM8tOUg899FCZgU1Z6tSpo7Nnz5a5jM4Z39PKfhfLU/K9cNT9/qgkjPmzpUsl4aCvr2+Zu6IBAIyPwAYAAINp2rSpmjVrpsOHD+uLL77Q22+//afjFy1apIKCAnl5eVmWQly5La+1xqb29FOpjJKeKmU1V7W2i401a9eu1fHjxxUUFKQFCxZcFY7k5eU5bHcqk8mku+66S/PmzVNcXJy8vLx06dIl9ezZs9Sshjp16qhevXrKzMzUkSNHrPacuXTpkrZu3arw8HDdcMMNVnvMVNbXX3+t/Px8dezYUbNnz77qNU6fPl3mtd99952++eYb+fr6atq0aZY+RX+0a9cuJSQkyNfXV99++63VZsB/9jplady4sc6ePasDBw5Y3cK7Mg2k/8hR38XylMyQK6v5snS5gbGXl5fGjBlj6Utkq5JeM7/99luZY0pmWjVo0MCuewMAjIWmwwAAGFDJzj6xsbGKi4src1xycrJmzJghSXrwwQctu++UNICVVKqHSYl169Y5stwyldRhrYaUlBQlJibadJ/U1FRJlxsfW5vJsnjxYssynSv7iXh7////q2PPUo+S3ZjWrVtn2eb4yt2hSpQ0or1ym+0rLV26VE899ZT69u2rnJwcm1/fHiWfTWRkpNVAaMGCBZY/X/nZbNu2TRMnTpQkjRs3Th06dCj3NWrXrm01rPnxxx8t/XzsaZbdo0cPSdL3339/Ve+UoqIiLV682OZ7lcdR38XytGvXTv7+/kpLS9NPP/101fmjR49q3bp1io+Pt/y8lvS6seU72qVLF3l7e+vXX3+1uqPTpUuXLN9HR806AwC4BoENAAAG1Lt3b91zzz0qKirSqFGjNG3aNGVmZlrOFxUVafXq1Ro8eLCysrIUERGhv/3tb5bztWrVsiylmjp1qmWJRGFhob766istWrSoSt5HdHS0pMtLhlatWmU5fuLECY0ePdrmBqclsxYSExNLhU0FBQWaP3++ZatkqXRD3iv7iJw8edKuuhs2bKitW7dq+/btCgkJUadOna4a98wzz6hGjRpaunSppk6dWuq1N2/ebAlEBg4c6LR+LCWfzfLly3X8+HHL8fPnz+utt97SDz/8YDlWUl9ycrJGjx6tgoICDRo0SI8//rhNr3H+/Hn973//sxwvKirSmjVrNGbMGMsxe7aqfvDBBxUWFqb9+/drwoQJliVQeXl5ev311/90Fom9HPVdLE9gYKCl99Err7yiffv2Wc6lpKRYtnq/7777LIFNycwtW76jN9xwgyVQfOGFF0qFNhcuXNDf//53/frrr6pbt66eeeYZh7wnAIBrsCQKAACDevvtt1WzZk0tWLBAs2bN0ieffKLw8HAFBgYqOTnZ0mC3bdu2mjlz5lXbcI8ePVqjRo3S9u3b1bVrV0VEROjUqVPKzMzUE088oYULF9rVCLciunfvrrZt22rPnj0aPXq0IiIiZDKZdOTIEdWtW1cPP/xwqQCgLD179lSrVq20f/9+Pffcc2rQoIHq1Kmj5ORkXbhwQUFBQWrYsKESExNLLfcKCgrSddddp9OnT+vRRx9VgwYN9M4776h58+blvuZ9992nmTNnSrq8Pbe12SvNmjXT5MmTNXbsWH300Uf6+uuv1bhxY507d84yK6VTp056+eWXbf3I7PbUU09p6dKlSk9PV+/evdWkSRNJl3cIys/PV4sWLXT69GllZWUpPT1dISEhmjRpks6dOydvb2+lp6fr6aef1sWLF62GFhMmTFCbNm3Uo0cPxcXF6Y033tDHH3+sa6+9VidPnlRmZqb8/f11880365dffrFruV1AQICmTp2qYcOGacGCBVq9erUaNWqk48eP68KFC+rWrZtl6/TKctR30RYvvPCCDh06pPj4eA0YMEBNmjSRr6+vkpKSVFBQoFatWmn8+PGW8SXh6r59+xQTE6PIyEhNnz69zPtPmDBBqamp2rp1qwYNGqSIiAjVrl1bhw8fVl5enoKCgvTBBx/ouuuuc8j7AQC4BjNsAAAwKJPJpEmTJmnevHkaOHCgGjZsqIyMDB04cEB+fn7q2rWrpkyZom+//dbqlsM9e/bUl19+aVlCcfToUd1www1699139eqrr1bJe/Dx8dEXX3yh4cOHq1GjRkpNTdW5c+fUr18/xcbGWl1eY42vr6++/vprjRgxQs2bN9eZM2d09OhRhYSEaMiQIVq6dKkefvhhSVcv95o+fbratGmjixcvKjk52bLtcnmuXAJ15e5Qf3T33XcrNjZWDzzwgIKCgpSYmKhz586pTZs2evXVV/XJJ5+UuzNPZTRo0ECxsbHq16+frr/+eiUlJenUqVNq0aKFxo8fr/nz5+v222+XJEv4UdLkt6ioSOvXr9fmzZu1Y8cOJSQkXPW/klBv2rRpGj9+vG666SZlZ2fr4MGDCgwM1KBBgxQbG6tRo0ZJkuLj4+2ardKuXTstXLhQ/fv3V61atXTw4EGFh4drypQplmfqCI76LtrCZDLpww8/1L/+9S/dcsstSktLU1JSkho1aqQXXnhBc+fOLbVssVOnThozZoyuu+46paamav/+/X/6GdaqVUufffaZJk6cqOjoaJ05c0ZHjhxReHi4hg4dqiVLlqhjx44Oez8AANfwKmbvPgAAAAAAAENhhg0AAAAAAIDBENgAAAAAAAAYDIENAAAAAACAwRDYAAAAAAAAGAyBDQAAAAAAgMEQ2AAAAAAAABgMgQ0AAAAAAIDBENgAAAAAAAAYDIENAAAAAACAwRDYAAAAAAAAGAyBDQAAAAAAgMH4uroAVA8ZGdmuLsFmISGBktyrZlQMz9pz8Kw9A8/Zc/CsPQfP2nPwrD0Hz/pqJZ+JvZhhAwAAAAAAYDAENgAAAAAAAAZDYAMAAAAAAGAwBDYAAAAAAAAGQ2ADAAAAAABgMAQ2AAAAAAAABkNgAwAAAAAAYDAENgAAAAAAAAZDYAMAAAAAAGAwBDYAAAAAAAAGQ2ADAAAAAABgMAQ2AAAAAAAABkNgAwAAAAAAYDAENgAAAAAAAAZDYAMAAAAAAGAwBDYAAAAAAAAGQ2ADAAAAAABgMAQ2AAAAAAA42OzZH6tz5/YaNWqYiouLrY7Jzs5W587tNXLks1bPx8WtVufO7dW1awedOXPGmeVW2m+/7de2bT9b/n7q1El17txe48e/5MKqpG3bftZvv+13aQ0VRWADAAAAAICT7Nq1U8uWLa7QtStXLlPNmjV16dIlrVix1MGVOc6WLZs1bNhTOnbsqOVYQECgnnpqqHr0+KvL6lq0aIHGjBmpjIwMl9VQGQQ2AAAAAAA40X/+M12ZmWftuubcuUxt2/az7rqrj6655hr98MPiMmfquFpW1jkVFRWVOhYYGKinnx6mnj1jXFSV7P7MjYbABgAAAAAAJ7nxxkhlZ1/QBx9Mseu61atX6NKlS/rLX25Tly53KjU1Rbt27XRSlTAiX1cXAAAAAABAdfXII09o9uyPtW7dGsXE9Nbtt3ex6bqVK5fJ19dX0dHtFRgYqNjY77V0aayio9tXuqazZ8/o888/1Y8/blRW1jlde22IunXrqSeffFq1atW2jCssLNRXX32m+Ph1SklJlslUQzfd1FIPP/y42re/VZI0adLrWrHiB0nS9Onva8SIYZIu97AZOPA+denSVW+//W/L2NWrV2jJklX66KOZ2rRpg/Ly8tWmTVu99NIrCgkJ1aeffqRVq5YrNzdXkZEtNHr0S2re/MZS9f/44yYtXDhfiYm/Kjs7W4GBgWrT5mYNGfKsmjePlCSNHPmsdu9OkCS9+urLkqTNm3dY7rFu3Vp9993/dOTIIXl5eeumm1rqiSeedsjn6yjMsAEAAAAAwEn8/EwaN+6f8vLy0r///Y5ycn4v95qjRw/r0KGDuvXWjgoMDFRUVLSuvTZE8fHrdeHChUrVc/r0aQ0d+oQWL/5ekZEt9OCDD6tBg0b63/++0siRzyo3N9cy9oMP3tNnn32iwMA6GjBgkLp376lff92nl14apYSEy+FHly53qkuXrpKkW2/tWO7rFxcXa/To4dq7d4/uvvtetWnTVtu2/ayxY1/UP/85TuvWrVG3bj3VoUNH7dq1U2PHvqiLFy9arv/++3kaN+5vSkk5oZ49Y/Tggw8rIqKJNm2K14gRz1qaM/fufa+ioqIlST169NJTTw213OPTTz/Sa6+9orNnz+juu+/R3Xf3UVLSUb344vNatWp5pT5fR2KGDQAAAACgSmTn5GvRpiSdOlN+aOFK119bW/3vaKIAfz+H3O/mm2/Rvff21ZIli/TJJ7P04ot//9PxK1YskyRL/xdvb2/16NFL8+b9T6tXL9cDDzxU4Vr+/e+3lZGRrnfeeb/UbJ/587/VtGlT9Pnnn+j551/Q77+btWTJIkVFRWvmzE8s4+69t6+eeeZxLVw4X9HR7XXHHXf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\n",
      "text/plain": [
       "<Figure size 576x396 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 406,
       "width": 566
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "T = df['tenure']\n",
    "E = df['churn']\n",
    "\n",
    "naf = NelsonAalenFitter()\n",
    "naf.fit(T, event_observed=E)\n",
    "\n",
    "naf.plot(at_risk_counts=True)\n",
    "plt.title('Cumulative hazard function');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NA_estimate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>timeline</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>0.055550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>0.074896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>0.090219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>0.104193</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          NA_estimate\n",
       "timeline             \n",
       "0.0          0.000000\n",
       "1.0          0.055550\n",
       "2.0          0.074896\n",
       "3.0          0.090219\n",
       "4.0          0.104193"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# display cumulative hazard\n",
    "naf.cumulative_hazard_.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>removed</th>\n",
       "      <th>observed</th>\n",
       "      <th>censored</th>\n",
       "      <th>entrance</th>\n",
       "      <th>at_risk</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event_at</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>7043</td>\n",
       "      <td>7043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>613</td>\n",
       "      <td>380</td>\n",
       "      <td>233</td>\n",
       "      <td>0</td>\n",
       "      <td>7032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>238</td>\n",
       "      <td>123</td>\n",
       "      <td>115</td>\n",
       "      <td>0</td>\n",
       "      <td>6419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>200</td>\n",
       "      <td>94</td>\n",
       "      <td>106</td>\n",
       "      <td>0</td>\n",
       "      <td>6181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>176</td>\n",
       "      <td>83</td>\n",
       "      <td>93</td>\n",
       "      <td>0</td>\n",
       "      <td>5981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>100</td>\n",
       "      <td>9</td>\n",
       "      <td>91</td>\n",
       "      <td>0</td>\n",
       "      <td>846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>95</td>\n",
       "      <td>8</td>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "      <td>746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>119</td>\n",
       "      <td>11</td>\n",
       "      <td>108</td>\n",
       "      <td>0</td>\n",
       "      <td>651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>170</td>\n",
       "      <td>6</td>\n",
       "      <td>164</td>\n",
       "      <td>0</td>\n",
       "      <td>532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>362</td>\n",
       "      <td>6</td>\n",
       "      <td>356</td>\n",
       "      <td>0</td>\n",
       "      <td>362</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          removed  observed  censored  entrance  at_risk\n",
       "event_at                                                \n",
       "0              11         0        11      7043     7043\n",
       "1             613       380       233         0     7032\n",
       "2             238       123       115         0     6419\n",
       "3             200        94       106         0     6181\n",
       "4             176        83        93         0     5981\n",
       "...           ...       ...       ...       ...      ...\n",
       "68            100         9        91         0      846\n",
       "69             95         8        87         0      746\n",
       "70            119        11       108         0      651\n",
       "71            170         6       164         0      532\n",
       "72            362         6       356         0      362\n",
       "\n",
       "[73 rows x 5 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# display the event table \n",
    "naf.event_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hazard functions for each payment method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Electronic check             2365\n",
       "Mailed check                 1612\n",
       "Bank transfer (automatic)    1544\n",
       "Credit card (automatic)      1522\n",
       "Name: PaymentMethod, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['PaymentMethod'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 358,
       "width": 481
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.subplot(111)\n",
    "\n",
    "naf = NelsonAalenFitter()\n",
    "\n",
    "for payment_method in df['PaymentMethod'].unique():\n",
    "    \n",
    "    flag = df['PaymentMethod'] == payment_method\n",
    "    \n",
    "    naf.fit(T[flag], event_observed=E[flag], label=payment_method)\n",
    "    naf.plot(ax=ax)\n",
    "\n",
    "plt.title('Cumulative hazard functions by payment method');"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
